FGC: the need for HIT-GIS and spatial analysis in Managed Care

Posted by Brian Altonen, MPH, MS under Uncategorized Comments Off on FGC: the need for HIT-GIS and spatial analysis in Managed Care

[reposted from LinkedIn]

It was only a matter of time before the findings and warnings I posted about female genital cutting (FGC) or manipulation surfaced in the form of actual case evidence via the news [links to these are at the end of this article].

FGC is a non-essential health practice that has been documented in the United States medical literature for more than 200 years. The first article documenting this practice in the U.S. is found in the Medical Repository, a medical journal linked to the first U.S. medical school(s) in New York, in which two cases involving late 18th century slaves were reported (see this article is at A disease peculiar to the children of negro slaves (1810).

The more recent attempts to publicize this practice with hopes for change, involved supermodel Waris Dirie, and Jaha Dukereh, who was highly active with the UN in 2015.

FGC or FGM is an example of a “culturally-bound” medical practice, and has its parallels with other such practices performed by other cultures. (For example, see my “FGM: Is it already here?” of June 6, 2016). The problem is, the long term effects of FGC are not considered when this practice is engaged in. In an interagency statement, the World Health Organization and others have asked that this practice be ceased [the resolution]. In a very recent conference devoted to this topic (March 13-14, 2017, Geneva, Switzerland), important updates were shared, including a report on the New York area (“Women Speak Out: Female Genital Cutting”, by Camille Clare, MD, et al., NY College of Medicine, Valhalla, NY).

In my national study of FGM (performed about 7-10 years ago, and charted for a population 0-85 yo), several age groups (age +/- 2 yrs) demonstrated greater amounts of reporting of this phenomenon in the EMR, for a 6+ year time frame evaluated for population consisting of MCR, MCD and commercially insured patients.

The following depicts the annual reporting rates for the most recent six years, as described by these data (left depicts rates. right depicts n; each n graphed as an age pyramid is preceded by total population N adjusted incidence/prevalence graph; using rolling 3 year averages, with number for age range 0-85 (cases>85 yo were excluded), graphed as rolling avgs, for ages 1 – 84):

My recent study of a large urban setting confirmed these findings, and demonstrated the possibility of an internal US practice being performed of this procedure, due to the number of children between 0 and 2 years of age found in both of my large population datasets evaluated for this ICD group. Both zip code and grid cell clustering techniques were applied to this work, using the 3D mapping technique I developed just prior to my studies.

The recent news articles on this topic pertaining to Michigan confirm my findings pn the “hot spots” for this practice in this country, according to the national EMR information that I reviewed, i.e. (but also see 3D video links that follow in the text].

This use of 3D mapping demonstrates the value of spatial analysis and the need to apply it, for a more thorough evaluation of its use in evaluating national EMR data.

The first maps developed using this non-GIS mapping methodology demonstrated how fast it can be used to produce outcomes, which were focused on presumably “the rarest of reported ICDs”. I used this technique to map out the distribution of ICD9-identified Sickle Cell and Sickle Cell carriers, and the other African American culture–ICD9-identified female genital cutting cases. This algorithm was then developed one step further, and used to produce videos of these results (see Sickle Cell (my see personal blog page on this), and FGM (the prototype and modified version).

This technique may also be used to identify hot spots for “immunization refusals” in this country (posted 6-12 months before the 2013 and 2014 small pox outbreak, and used to predict the recent spread of this disease due to immunization refusal behavior). [Review this SEARCH for those links]. It has also been applied to the study of Ebola behavior, using a method applicable to researching other international, zoonotic disease patterns [for which see].

Many of the “outbreaks” striking the news, now or in the future, are understandable and even predictable by requiring and then integrating EMR/HIT protocols with GIS and Spatial Analysis protocols within all managed care systems, at both the facility and business levels.

For an example of such a system devoted to health conditions as cultural phenomena, begin with my “Socioculturalism and Health” page. This anthropological interpretation of culturally related health care conditions, however, represents just one view of how culture affects the human health state. In effect, it is proposed that we analyze ‘culture’ and health as a four part model: i) review socially, culturally, geographically linked ecological conditions such as culturally-related infectious and human ecological diseases, ii) review socioculturally-linked human ecological/behavioral diseases, iii) review socioculturally- (or culturally-) linked ecological/biological diseases (which the present genomic and epigenomic study of disease is now eluding to), and iv) review the classic culturally-bound disease patterns. Several years ago this method was discussed extensively on several pages, beginning with “Applying culture to managed care metrics.”

The following links pertain to the present FGC or FGM events, and were reviewed for this posting (links are provided in temporal order, and were active on 4/30/2017]. They are followed by several more links to helpful readings.